Data Scientist

INTRODUCTION

elseco is a high-technology specialty underwriting agency and Lloyd's Coverholder operating at the forefront of complex global risk.

Founded 20 years ago as a specialist space underwriting platform, elseco has grown into a diversified multi-line MGA spanning Space, Aviation, Energy and Accident & Health. Today, we are recognised as a global leader in Space Insurance, representing the largest insurance capacity in the world dedicated to Space risks. In Aviation, we are regarded amongst the most technically recognised underwriting markets globally, trusted to price and structure some of the most sophisticated airline and aerospace portfolios.

We trade in excess of USD 220 million in premium annually on behalf of more than 50 insurance and reinsurance partners, including leading Lloyd's syndicates. Headquartered in the Dubai International Financial Centre and regulated by the Dubai Financial Services Authority, with a regulated presence in London, our team brings together more than 130 professionals across underwriting, analytics, technology and operations.

What differentiates elseco is discipline and intellectual rigour. Our underwriting philosophy is evidence-based, transparent and technically demanding. Over two decades, we have built extensive, state-of-the-art proprietary databases covering satellite launches, in-orbit performance, aviation operations and complex specialty risks. These datasets are among the most comprehensive in the market and form the backbone of our analytical advantage. We do not follow market sentiment we lead through data insight.

At the heart of this capability sits elselab, our integrated Research & Development function. elselab brings together data scientists, actuaries and engineers working directly alongside underwriters to transform complex data into real underwriting decisions. Our team combines strong academic foundations with real-world impact and includes graduates from leading international universities with backgrounds in data science, mathematics, physics, engineering and actuarial science.

This is not a narrow modelling role. The work is diverse and spans pricing model development, portfolio analytics, statistical research, risk simulation, data engineering and strategic underwriting support across multiple lines of business. The output directly influences pricing, portfolio construction and capital allocation across a global underwriting platform.

We are entering a new phase of growth expanding existing lines, developing new specialty segments and continuously enhancing our technological infrastructure. For individuals motivated by intellectual challenge, tangible impact and long-term ambition, elselab offers a rare opportunity to build models that shape real-world markets.

Job Purpose

Reporting to the Head of elselab and working in close collaboration with software developers, data engineers and underwriting teams, the Data Scientist will play a central role in transforming data into underwriting intelligence.

The position sits at the intersection of analytics, technology and decision-making. The successful candidate will actively contribute to the analysis of complex proprietary datasets, the design and development of advanced statistical and machine learning models, and the construction of business intelligence tools that directly support pricing, portfolio management and capital allocation.

This role requires strong analytical capabilities, intellectual curiosity and a rigorous approach to problem-solving. The Data Scientist will leverage statistical modelling, modern AI techniques and structured experimentation to extract signal from complex risk data and convert it into actionable insights embedded within our underwriting platform.

The mandate is not limited to theoretical modelling. It includes taking ideas from research to implementation working alongside developers to industrialise models, integrate them into production systems and ensure their robustness and interpretability in a real underwriting environment.

This is a high-visibility role within a data-led underwriting organisation, offering direct exposure to senior decision-makers and measurable impact on portfolio performance across global specialty lines.

SPECIFIC DUTIES AND RESPONSIBILITIES

• Explore and analyse complex proprietary datasets to extract insights that support underwriting, pricing and portfolio decisions.
• Develop statistical and machine learning models to enhance risk assessment, pricing strategies and portfolio analytics across specialty insurance lines.
• Work closely with underwriters to translate business questions into analytical approaches and practical modelling solutions.
• Collaborate with data engineers and software developers to ensure models are correctly implemented, integrated and usable within production systems.
• Clearly communicate analytical findings to both technical and non-technical stakeholders, ensuring models are well understood and effectively adopted.
• Structure analytical work into manageable tasks and contribute to delivering high-quality outputs within agreed timelines.
• Continuously develop technical skills and remain curious about new techniques, tools and approaches in data science and machine learning.

KNOWLEDGE AND SKILLS

• Master's degree in Data Science, Mathematics, Statistics, Economics, Physics, Engineering or a related quantitative discipline.
• PhD candidates and candidates progressing through an actuarial qualification pathway are also encouraged to apply.
• Internship experience or 25 years of professional experience in data science, analytics, statistics or pricing, ideally within financial services or insurance.
• Strong academic track record demonstrating analytical rigour and intellectual curiosity.
• Solid programming skills in Python and a good understanding of statistical modelling and machine learning.
• Excellent written and spoken English, with the ability to communicate complex ideas clearly and effectively.
• Curious, rigorous and eager to learn, motivated by solving challenging problems and continuously developing new skills.
• Ability to deliver high-quality work in a fast-paced environment, managing priorities and meeting demanding deadlines.
• Strong team spirit and collaborative mindset, with enthusiasm for contributing to a supportive and hard-working multicultural team.